The consequences of statistical tests on proxy variables, an application to short-TE as an estimation for MEGA-edited GABA

Motivation: Certain studies use short-TE MRS to estimate metabolites such as gamma-aminobutyric acid. The findings of such studies hinge on the correlation of this technique to the gold-standard edited MRS technique. Goal(s): We investigate how the false negative rate and false positive rate of studies vary as a function of correlation between short-TE and MEGA-edited metabolite estimates. Approach: Simulated data was used to numerically estimate the false positive and false negative rates, using parameters obtained from the literature. Results: We show that these studies can have largely inflated false positive and false negative rates as compared to their nominally designed values. Impact: The false negative and false positive rate can be markedly inflated when using short-TE MRS to estimate metabolites such as gamma-aminobutyric acid. This calls for increased caution in interpreting results, and the accommodation of these effects when designing statistical analyses.